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Ordinary least squares

Known as: Ordinary Least Squares Regression, Least-squares estimation of linear regression coefficients, Normal equation 
In statistics, ordinary least squares (OLS) or linear least squares is a method for estimating the unknown parameters in a linear regression model… Expand
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Papers overview

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2017
2017
Linear regression is one of the most prevalent techniques in machine learning, however, it is also common to use linear… Expand
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Highly Cited
2010
Highly Cited
2010
Data envelopment analysis (DEA) is known as a nonparametric mathematical programming approach to productive efficiency analysis… Expand
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Highly Cited
2009
Highly Cited
2009
The paper examines second stage DEA efficiency analyses, within the context of a censoring data generating process (DGP) and a… Expand
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Highly Cited
2007
Highly Cited
2007
Totla least squares (TLS) is a method of fitting that is appropriate when there are errors in both the observation vector $b (mxl… Expand
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Highly Cited
2007
Highly Cited
2007
We propose a method of least squares approximation (LSA) for unified yet simple LASSO estimation. Our general theoretical… Expand
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Highly Cited
2006
Highly Cited
2006
This note formalizes bias and inconsistency results for ordinary least squares (OLS) on the linear probability model and provides… Expand
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Highly Cited
2005
Highly Cited
2005
  • Sukumar Mishra
  • IEEE Transactions on Evolutionary Computation
  • 2005
  • Corpus ID: 10318807
Harmonic estimation for a signal distorted with additive noise has been an area of interest for researchers in many disciplines… Expand
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Highly Cited
1990
Highly Cited
1990
This paper derives the asymptotic distribution for a vector of sample autocorrelations of regression residuals from a quite… Expand
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Highly Cited
1990
Highly Cited
1990
[Read before The Royal Statistical Society at a meeting organized by the Research Section on Wednesday, October 25th, 1989… Expand
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Highly Cited
1987
Highly Cited
1987
Time series variables that stochastically trend together form a cointegrated system. OLS and NLS estimators of the parameters of… Expand
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